Steering the governance of artificial intelligence: national strategies in perspective

As more and more governments release national strategies on artificial intelligence (AI), their priorities and modes of governance become more clear. This study proposes the first comprehensive analysis of national approaches to AI from a hybrid governance perspective, reflecting on the dominant reg...

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Veröffentlicht in:Policy & society Jg. 40; H. 2; S. 178 - 193
1. Verfasser: Radu, Roxana
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Singapore Routledge 03.04.2021
Oxford University Press
Schlagworte:
Analysis
Artificial intelligence
Content analysis
Discourses
Ethics
Governance
hybrid governance
Laws, regulations and rules
national AI strategies
Policy sciences
Property
Public sector private sector relations
regulation
Strategies
Technology and state
Switzerland
ISSN:1449-4035, 1839-3373, 1839-3373
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:As more and more governments release national strategies on artificial intelligence (AI), their priorities and modes of governance become more clear. This study proposes the first comprehensive analysis of national approaches to AI from a hybrid governance perspective, reflecting on the dominant regulatory discourses and the (re)definition of the public-private ordering in the making. It analyses national strategies released between 2017 and 2019, uncovering the plural institutional logics at play and the public-private interaction in the design of AI governance, from the drafting stage to the creation of new oversight institutions. Using qualitative content analysis, the strategies of a dozen countries (as diverse as Canada and China) are explored to determine how a hybrid configuration is set in place. The findings show a predominance of ethics-oriented rather than rule-based systems and a strong preference for functional indetermination as deliberate properties of hybrid AI governance.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1449-4035
1839-3373
1839-3373
DOI:10.1080/14494035.2021.1929728